Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing

Gerlinger, Marco; Horswell, Stuart; Larkin, James; Rowan, Andrew; Salm, Max; Varela, Ignacio; Fisher, Rosalie; McGranahan, Nicholas; Matthews, N.; Santos, Cláudio R.; Martinez, Pierre; Phillimore, Benjamin; Begum, Sharmin; Rabinowitz, Adam; Spencer‐Dene, Bradley; Gulati, Sakshi; Bates, Paul A.; Stamp, Gordon; Pickering, Lisa; Gore, Martin; Nicol, David; Hazell, Steven; Futreal, P. Andrew; Stewart, Aengus; Swanton, Charles

doi:10.1038/ng.2891

Cited by 1,130 publications

(1,261 citation statements)

References 43 publications

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“…Genomic heterogeneity of tumors, a phenomenon well described in mRCC (20) and common in patients treated with targeted therapy, may explain the mixed response seen in Case 4. Although some of the lesions were responding, a dominant resistant population of cells may have been present at baseline (soft tissue nodule, Fig.…”

Section: Discussionmentioning

confidence: 98%

Radiologic Heterogeneity in Responses to Anti–PD-1/PD-L1 Therapy in Metastatic Renal Cell Carcinoma

Velasco

Krajewski

Albigès

et al. 2016

Cancer Immunology Research

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Radiologic assessment of tumor response remains a challenge in patients treated with immune checkpoint inhibitors. In metastatic melanoma, for example, a spectrum of imaging patterns in response to immunotherapies have been recognized and associated with clinical benefit. In metastatic renal cell carcinoma (mRCC), less than half of patients treated with immune checkpoint inhibitors achieve objective responses, but some of the responses have been durable. In this series, five different imaging patterns of response and progression are described in mRCC patients treated with anti-PD-1/PD-L1 agents: (i) early and complete response, (ii) pseudoprogression, (iii) disease stability before ultimate response, (iv) mixed response with new lesions, and (v) early progression/primary refractory disease. The implications of the different imaging patterns of patient responses on disease prognosis are discussed and highlight the need for individualized patient assessment when using these novel immune-targeted agents.

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Section: Discussionmentioning

confidence: 98%

Radiologic Heterogeneity in Responses to Anti–PD-1/PD-L1 Therapy in Metastatic Renal Cell Carcinoma

Velasco

Krajewski

Albigès

et al. 2016

Cancer Immunology Research

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“…Such factors include the number of available samples, the number of somatic mutations in a sample, the number of mutations contributed by different mutational signatures, the similarity between the patterns of the signatures of mutational processes operative in cancer samples, as well as the computational limitations of our framework. Nevertheless, in the past three years, our framework has proven robust and has described multiple similar and validated signatures across the spectrum of human cancer [3][4][5][15][16][17][18][19][20][21][22] .…”

Section: Factors Influencing Signature Extractionmentioning

confidence: 99%

Clock-like mutational processes in human somatic cells

et al. 2015

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During the course of a lifetime somatic cells acquire mutations. Different mutational processes may contribute to the mutations accumulated in a cell, with each imprinting a mutational signature on the cell's genome. Some processes generate mutations throughout life at a constant rate in all individuals and the number of mutations in a cell attributable to these processes will be proportional to the chronological age of the person. Using mutations from 10,250 cancer genomes across 36 cancer types, we investigated clock-like mutational processes that have been operating in normal human cells. Two mutational signatures show clock-like properties. Both exhibit different mutation rates in different tissues. However, their mutation rates are not correlated indicating that the underlying processes are subject to different biological influences. For one signature, the rate of cell division may influence its mutation rate. This study provides the first survey of clock-like mutational processes operative in human somatic cells.

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“…Even with strict adherence to the 2014 National Comprehensive Cancer Network or American Urological Association surveillance guidelines, onethird of RCC recurrences will be missed [1]. Metastases of RCC tumors have been reported to virtually all organs; however, the most common sites are pulmonary and bone [2].…”

Section: Introductionmentioning

confidence: 99%

Differential gene expression profiling of matched primary renal cell carcinoma and metastases reveals upregulation of extracellular matrix genes

Serie²,

Parasramka³

et al. 2017

Annals of Oncology

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Background: The majority of renal cell carcinoma (RCC) studies analyze primary tumors, and the corresponding results are extrapolated to metastatic RCC tumors. However, it is unknown if gene expression profiles from primary RCC tumors differs from patient-matched metastatic tumors. Thus, we sought to identify differentially expressed genes between patient-matched primary and metastatic RCC tumors in order to understand the molecular mechanisms underlying the development of RCC metastases. Patients and methods:We compared gene expression profiles between patient-matched primary and metastatic RCC tumors using a two-stage design. First, we used Affymetrix microarrays on 15 pairs of primary RCC [14 clear cell RCC (ccRCC), 1 papillary] tumors and patient-matched pulmonary metastases. Second, we used a custom NanoString panel to validate seven candidate genes in an independent cohort of 114 ccRCC patients. Differential gene expression was evaluated using a mixed effect linear model; a random effect denoting patient was included to account for the paired data. Third, The Cancer Genome Atlas (TCGA) data were used to evaluate associations with metastasis-free and overall survival in primary ccRCC tumors.Results: We identified and validated up regulation of seven genes functionally involved in the formation of the extracellular matrix (ECM): DCN, SLIT2, LUM, LAMA2, ADAMTS12, CEACAM6 and LMO3. In primary ccRCC, CEACAM6 and LUM were significantly associated with metastasis-free and overall survival (P < 0.01). Conclusions:We evaluated gene expression profiles using the largest set to date, to our knowledge, of patient-matched primary and metastatic ccRCC tumors and identified up regulation of ECM genes in metastases. Our study implicates up regulation of ECM genes as a critical molecular event leading to visceral, bone and soft tissue metastases in ccRCC.

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Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing

Cited by 1,130 publications

References 43 publications

Radiologic Heterogeneity in Responses to Anti–PD-1/PD-L1 Therapy in Metastatic Renal Cell Carcinoma

Radiologic Heterogeneity in Responses to Anti–PD-1/PD-L1 Therapy in Metastatic Renal Cell Carcinoma

Clock-like mutational processes in human somatic cells

Differential gene expression profiling of matched primary renal cell carcinoma and metastases reveals upregulation of extracellular matrix genes

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